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Web application for mining areas polygonization DOI

This web application supports the delineation (polygonization) of mining areas using satellite images given a set of approximate locations where mining may occur. The app systematically displays the mining locations and several background options of satellite images, which the users can take into account to draw and edit polygons.

The app is built in R Shiny with a PostgreSQL Database and PostGIS extension. The app and database can either be created with one single docker-compose command or, the application the current setup is targeting:, the database is set up using docker-compose, and the application itself is deployed via shinyproxy in order to allow user management and password protection (see details below).

Note: The app requires a database as defined in create_db_schema.sql. The database must be populated with approximate mining locations and other information about the mines.

Usage

  1. Dependencies
  2. Get the app
  3. Setup
  4. How to run
  5. How to restart/stop

Dependencies

In order to run the app, you need the following tools installed:

Docker and Docker Compose

To install Docker and Docker Compose (comes already installed with Docker Desktop) for you system follow the links below:

(git)

You only need git installed if you want to contribute to the repository or clone it without having to download it manually.

(R and RStudio)

You only need R (version 3.5 or higher) and RStudio installed in case you would like to make your own changes to the app and try them out before you create the docker containers.

If you are on a Linux machine, you need to install the following packages via apt (or any other package manager) as they are required by the R packages needed: sudo apt install libpq-dev libssl-dev libxml2-dev libcurl4-openssl-dev

The command to install the R packages can be found on the respective file you want to edit.

ShinyProxy

To use the app with ShinyProxy, create a database with docker-compose and deploy the app within a ShinyProxy environment, refer to our brief shinyproxy-documentation.

Get the app

To get the app, you can either

  • download the source using the "Clone or download"-button above
  • use git clone https://github.com/fineprint-global/app-mining-area-polygonization.git

Setup

There are a few settings that you have to make before you can run the app.

.env file in the root directory

You have to set the following variables, here is an example .env file:

POSTGRES_PASSWORD=postgresuserpassword
POSTGRES_PORT=5454
SHINY_PORT=80

.Renviron file in the /app directory

In the .Renviron file, you need to set the internal container port as your db_port, so DO NOT match the POSTGRES_PORT in the .env file, but set the default port for postgres, which is 5432. Here is an example file that needs to be created inside the /app directory.

db_host=mva_db
db_port=5432
db_name=vector_mine
db_user=app
db_password=YOURPASSWORD

In case you would want to work with the insert_mines_to_db.R script, you also need to add the following lines to the .Renviron in the data-to-db folder:

db_admin_user=postgres
db_admin_password=postgresuserpassword

How to run

Please note that this how-to-run only applies to usage with docker-compose for both, not yet to our ShinyProxy deployment.

  1. You can run it as is, with a pre-loaded database.
  2. You can use your own data, which requires you to adapt the scripts in the data-to-db directory.
  3. You can leave the database as is and change the visualizations.

1. Run as is

  1. Make sure all necessary dependencies are installed.
  2. Make sure Docker (Desktop) is up and running.
  3. Make sure you completed the steps in setup
  4. Navigate to the root directory (app-mining-area-polygonization) with a shell of your choice and run the following command: docker-compose up -d

Now both, the mva_app (RShiny app) and the mva_db (postgis database) should be running on ports specified in the docker-compose.yml on your localhost (e.g. ports 80 and 5454 respectively). To verify that both containers are running and the ports are correct, you can run docker-compose ps (in the root directory) or docker ps (anywhere).

You should now be able to see the app running at localhost:80 or – if not 80 – at the port you specified in SHINY_PORT.

If there are any problems, check out the troubleshooting section.

2. Use your own data

More detailed instructions on this will come soon, but you will have to adjust the insert_mines_to_db.R located in the data-to-db directory to load your own input-output table and adjust it to the proper database format.

3. Change the visualizations

The folders to take care of are the app folder and the docker-rshiny folder. The app folder will be used to change the visualizations whereas the docker-rshiny folder needs to be kept in mind for any new packages you might require.

3.1 app folder

Before you dive into this, if you are new to RShiny, you may want to check out this tutorial.

Our app is divided into 4 main files:

  • app.R: you should not need to add anything there, this just brings all three other files together
  • global.R: this will be executed once for every worker process, not for every user, so this is where you specify database connections and perform other setup-related tasks
  • ui.R: you specify the UI here. output elements (e.g. uiOutput) are defined here and respective render functions (e.g. renderText) for those are performed in the server.R. If you want to add new visualizations or other elements, define them here.
  • server.R: any new visualizations defined in the ui.R should be implemented in the server.R, this is where you collect your data, bring it into the correct format and then define the output-layout (e.g. for plotly).
3.2 docker-rshiny folder for packages

You need to edit the Dockerfile if you add any new packages that are not included yet.

3.3 post-processing folder

This folder contains the R scripts to create a mining polygons data release.

How to restart or stop the app

  • To restart the containers, run docker-compose restart
  • To stop the containers, move to the app-mining-area-polygonization directory and run docker-compose stop
  • To stop containers and to remove containers, networks, volumes, and images created by docker-compose up, run docker-compose down

Troubleshooting

This section is still to come.

  • make sure you have all dependencies (packages etc.) installed, you may want to check out the RShiny Dockerfile for any packages necessary for the app to run

Windows-Issues with RShiny Docker

In case there are issues with building and running the RShiny Docker from the directory (especially in Windows file permissions tend to get messed up, and then the container is constantly restarting, sometimes with the error: standard_init_linux.go:207: exec user process caused "no such file or directory"), you can alternatively use the docker image from Docker Hub. For this, you need to replace the build context with the Docker Hub image like below:

    # build:
    #   context: ./docker-rshiny
    image: fineprint/mva

Acknowledgement

This work was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme grant number 725525 FINEPRINT project.